Total Variation Based Perceptual Image Quality Assessment Modeling
Visual quality measure is one of the fundamental and important issues to numerous applications of image and video processing. In this paper, based on the assumption that human visual system is sensitive to image structures (edges) and image local luminance (light stimulation), we propose a new perce...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2014/294870 |
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| author | Yadong Wu Hongying Zhang Ran Duan |
| author_facet | Yadong Wu Hongying Zhang Ran Duan |
| author_sort | Yadong Wu |
| collection | DOAJ |
| description | Visual quality measure is one of the fundamental and important issues to numerous applications of image and video processing. In this paper, based on the assumption that human visual system is sensitive to image structures (edges) and image local luminance (light stimulation), we propose a new perceptual image quality assessment (PIQA) measure based on total variation (TV) model (TVPIQA) in spatial domain. The proposed measure compares TVs between a distorted image and its reference image to represent the loss of image structural information. Because of the good performance of TV model in describing edges, the proposed TVPIQA measure can illustrate image structure information very well. In addition, the energy of enclosed regions in a difference image between the reference image and its distorted image is used to measure the missing luminance information which is sensitive to human visual system. Finally, we validate the performance of TVPIQA measure with Cornell-A57, IVC, TID2008, and CSIQ databases and show that TVPIQA measure outperforms recent state-of-the-art image quality assessment measures. |
| format | Article |
| id | doaj-art-e2c0a7ad79d14db58a539cde9c3edf50 |
| institution | Kabale University |
| issn | 1110-757X 1687-0042 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Applied Mathematics |
| spelling | doaj-art-e2c0a7ad79d14db58a539cde9c3edf502025-02-03T01:23:32ZengWileyJournal of Applied Mathematics1110-757X1687-00422014-01-01201410.1155/2014/294870294870Total Variation Based Perceptual Image Quality Assessment ModelingYadong Wu0Hongying Zhang1Ran Duan2School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang 621010, ChinaRobot Technology Used for Special Environment Key Laboratory of Sichuan Province, School of Information and Engineering, Southwest University of Science and Technology, Mianyang 621010, ChinaRobot Technology Used for Special Environment Key Laboratory of Sichuan Province, School of Information and Engineering, Southwest University of Science and Technology, Mianyang 621010, ChinaVisual quality measure is one of the fundamental and important issues to numerous applications of image and video processing. In this paper, based on the assumption that human visual system is sensitive to image structures (edges) and image local luminance (light stimulation), we propose a new perceptual image quality assessment (PIQA) measure based on total variation (TV) model (TVPIQA) in spatial domain. The proposed measure compares TVs between a distorted image and its reference image to represent the loss of image structural information. Because of the good performance of TV model in describing edges, the proposed TVPIQA measure can illustrate image structure information very well. In addition, the energy of enclosed regions in a difference image between the reference image and its distorted image is used to measure the missing luminance information which is sensitive to human visual system. Finally, we validate the performance of TVPIQA measure with Cornell-A57, IVC, TID2008, and CSIQ databases and show that TVPIQA measure outperforms recent state-of-the-art image quality assessment measures.http://dx.doi.org/10.1155/2014/294870 |
| spellingShingle | Yadong Wu Hongying Zhang Ran Duan Total Variation Based Perceptual Image Quality Assessment Modeling Journal of Applied Mathematics |
| title | Total Variation Based Perceptual Image Quality Assessment Modeling |
| title_full | Total Variation Based Perceptual Image Quality Assessment Modeling |
| title_fullStr | Total Variation Based Perceptual Image Quality Assessment Modeling |
| title_full_unstemmed | Total Variation Based Perceptual Image Quality Assessment Modeling |
| title_short | Total Variation Based Perceptual Image Quality Assessment Modeling |
| title_sort | total variation based perceptual image quality assessment modeling |
| url | http://dx.doi.org/10.1155/2014/294870 |
| work_keys_str_mv | AT yadongwu totalvariationbasedperceptualimagequalityassessmentmodeling AT hongyingzhang totalvariationbasedperceptualimagequalityassessmentmodeling AT randuan totalvariationbasedperceptualimagequalityassessmentmodeling |